Short time-series microarray analysis: Methods and challenges

The detection and analysis of steady-state gene expression has become routine. Time-series microarrays are of growing interest to systems biologists for deciphering the dynamic nature and complex regulation of biosystems. Most temporal microarray data only contain a limited number of time points, giving rise to short-time-series data, which imposes challenges for traditional methods of extracting meaningful information. To obtain useful information from the wealth of short-time series data requires addressing the problems that arise due to limited sampling. Current efforts have shown promise in improving the analysis of short time-series microarray data, although challenges remain. This commentary addresses recent advances in methods for short-time series analysis including simplification-based approaches and the integration of multi-source information. Nevertheless, further studies and development of computational methods are needed to provide practical solutions to fully exploit the potential of this data

Properties of localization in silicon-based lattice periodicity breaking photonic crystal waveguides

The light localization effects in silicon photonic crystal cavities at different disorder degrees have been studied using the finite difference time domain (FDTD) method in this paper. Numerical results showed that localization occurs and enhancement can be gained in the region of the cavity under certain conditions. The stabilities of the localization effects due to the structural perturbations have been investigated too. Detailed studies showed that when the degree of structural disorder is small(about 10%), the localization effects are stable, the maximum enhancement factor can reach 16.5 for incident wavelength of 785 nm and 23 for 850 nm in the cavity, with the degree of disorder about 8%. The equivalent diameter of the localized spot is almost constant at different disorder degrees, approximating to {\lambda \mathord{/ {\vphantom {\lambda 7}} \kern-\nulldelimiterspace} 7}λ/7, which turned out to be independent on the structural perturbation

Effects of magnanimous therapy on emotional, psychosomatic and immune functions of lung cancer patients

This study was a randomised controlled study on the effects of the individual computer magnanimous therapy and group computer magnanimous therapy on emotional, psychosomatic and immune function among advanced lung cancer patients. Patients were examined at baseline and 2 weeks later using the Psychosomatic Status Scale for Cancer Patients, Hospital Anxiety Depression Scale and IgA, IgG, IgM and natural killer cell functions. The results showed that individual computer magnanimous therapy and group computer magnanimous therapy were beneficial for advanced lung cancer patients in improving depression, anxiety, psychosomatic status and immune functions. The improvements of immune functions may be related to the improvements of the participants’ emotional and psychosocial status

Hydrological projections under CMIP5-6: sources and magnitudes of uncertainty

Projections of future hydrological conditions rely largely on global climate models, but model performance varies greatly. In this study, we investigated projected changes in runoff (R), precipitation (P), evapotranspiration (ET), and soil moisture (SM) based on the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) and quantified the uncertainties of their projected changes on annual and seasonal scales. The results indicate that all four hydrological variables show an increase over most of the global land: annual projections of R, P, ET, and SM from CMIP6 increase in 72%, 81%, 82%, and 66% of the global land area, respectively, under a high emissions scenario during the period 2080–99 relative to 1970–99. We estimated the uncertainties in CMIP6 from different sources on an annual scale and found that model uncertainty dominates the total projected uncertainties during the twenty-first century [76% (R), 73% (P), 89% (ET), and 95% (SM) in the 2090s], and the contribution of internal variability decreases with time. The low-latitude regions have the greatest uncertainty in hydrological projections. In CMIP6, the uncertainty of projected changes in P contributes the most to the uncertainty of projected changes in R, with a contribution of 93% on annual scale, followed by ET and SM. Overall, the performances of the CMIP5 and CMIP6 models are similar in terms of hydrological changes and the composition of their uncertainties. This study provides a theoretical reference for the further improvement and development of hydrological components in global climate models

SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

As an important and challenging problem in computer vision, PAnoramic Semantic Segmentation (PASS) gives complete scene perception based on an ultra-wide angle of view. Usually, prevalent PASS methods with 2D panoramic image input focus on solving image distortions but lack consideration of the 3D properties of original $360^{\circ}$ data. Therefore, their performance will drop a lot when inputting panoramic images with the 3D disturbance. To be more robust to 3D disturbance, we propose our Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation (SGAT4PASS), considering 3D spherical geometry knowledge. Specifically, a spherical geometry-aware framework is proposed for PASS. It includes three modules, i.e., spherical geometry-aware image projection, spherical deformable patch embedding, and a panorama-aware loss, which takes input images with 3D disturbance into account, adds a spherical geometry-aware constraint on the existing deformable patch embedding, and indicates the pixel density of original $360^{\circ}$ data, respectively. Experimental results on Stanford2D3D Panoramic datasets show that SGAT4PASS significantly improves performance and robustness, with approximately a 2% increase in mIoU, and when small 3D disturbances occur in the data, the stability of our performance is improved by an order of magnitude. Our code and supplementary material are available at https://github.com/TencentARC/SGAT4PASS.Comment: Accepted by IJCAI 202

Effects and mechanisms of a new multivitamin on chronic metabolic syndromes and aging

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Ecological functions of uncultured microorganisms in the cobalt-rich ferromanganese crust of a seamount in the central Pacific are elucidated by fosmid sequencing

Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Acta Oceanologica Sinica 34 (2015):92-113, doi:10.1007/s13131-015-0650-7.Cobalt-rich ferromanganese is an important seafloor mineral and is abundantly present in the seamount crusts. Such crusts form potential hotspots for biogeochemical activity and microbial diversity, yet our understanding of their microbial communities is lacking. In this study, we used a cultivation-independent approach to recover genomic information and derive ecological functions of the microbes in a sediment sample collected from the cobalt-rich ferromanganese crust of a seamount region in the central Pacific. A total of 78 distinct clones were obtained by fosmid library screening with a 16S rRNA based PCR method. Proteobacteria and MGI Thaumarchaeota dominated the bacterial and archaeal 16S rRNA gene sequence results in the microbial community. Nine fosmid clones were sequenced and annotated. Numerous genes encoding proteins involved in metabolic functions and heavy metal resistance were identified, suggesting alternative metabolic pathways and stress responses that are essential for microbial survival in the cobalt-rich ferromanganese crust. In addition, genes that participate in the synthesis of organic acids and exoploymers were discovered. Reconstruction of the metabolic pathways revealed that the nitrogen cycle is an important biogeochemical process in the cobalt-rich ferromanganese crust. In addition, horizontal gene transfer (HGT) events have been observed, and most of them came from bacteria, with some occurring in archaea and plants. Clone W4-93a, belonging to MGI Thaumarchaeota, contained a region of gene synteny. Comparative analyses suggested that a high frequency of HGT events as well as genomic divergence play important roles in the microbial adaption to the deep-sea environment.China Ocean Mineral Resources R & D Association (COMRA) Special Foundation (No. DY125-15-R-03 and DY125-13-E-01); the National Natural Science Foundation of China (No. 41276173); the Zhejiang Provincial Natural Science Foundation of China (No. LQ13D060002) and the Scientific Research Fund of the Second Institute of Oceanography, SOA (No. JT1305).2016-04-1